论文标题
多态项目响应模型的分类学
A Taxonomy of Polytomous Item Response Models
论文作者
论文摘要
提供了一个共同的框架，该框架包括经典的序数项目响应模型作为累积，顺序和相邻类别模型以及标称响应模型和项目响应树模型。分类法是基于可以将二进制模型视为各种模型的基础的方式。特别是可以区分条件和无条件模型组件。有条件模型是迄今为止包含相邻类别模型和整个层次结构化模型的较大类模型。后者作为一类模型引入，该模型包括二进制树和层次结构化模型，这些模型有条件地使用有条件的模型。潜在特征模型中包含的二进制模型的研究阐明了模型与项目参数的解释之间的关系。它也用于通过对序数模型的概念化来区分序数模型和名义模型。分类法与以前的分类法不同，通过关注二分法的结构化使用而不是参数化的作用。
A common framework is provided that comprises classical ordinal item response models as the cumulative, sequential and adjacent categories models as well as nominal response models and item response tree models. The taxonomy is based on the ways binary models can be seen as building blocks of the various models. In particular one can distinguish between conditional and unconditional model components. Conditional models are by far the larger class of models containing the adjacent categories model and the whole class of hierarchically structured models. The latter is introduced as a class of models that comprises binary trees and hierarchically structured models that use ordinal models conditionally. The study of the binary models contained in latent trait models clarifies the relation between models and the interpretation of item parameters. It is also used to distinguish between ordinal and nominal models by giving a conceptualization of ordinal models. The taxonomy differs from previous taxonomies by focusing on the structured use of dichotomizations instead of the role of parameterizations.
